A robust knowledge-based plant searching strategy
Expert Systems with Applications: An International Journal
Optimization of temporal processes: a model predictive control approach
IEEE Transactions on Evolutionary Computation - Special issue on computational finance and economics
Multiobjective optimization of temporal processes
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics - Special issue on game theory
Proceedings of the 11th International Conference on Computer Systems and Technologies and Workshop for PhD Students in Computing on International Conference on Computer Systems and Technologies
Expert Systems with Applications: An International Journal
Prediction of NOx emissions from a direct injection diesel engine using artificial neural network
Modelling and Simulation in Engineering
Advances in Artificial Intelligence
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Diesel engines are fuel efficient which benefits the reduction of CO2 released to the atmosphere compared with gasoline engines, but still result in negative environmental impact related to their emissions. As new degrees of freedom are created, due to advances in technology, the complicated processes of emission formation are difficult to assess. This paper studies the feasibility of using artificial neural networks (ANNs) in combination with genetic algorithms (GAs) to optimize the diesel engine settings. The objective of the optimization was to find settings that complied with the increasingly stringent emission regulations while also maintaining, or even reducing the fuel consumption. A large database of stationary engine tests, covering a wide range of experimental conditions was used for this analysis. The ANNs were used as a simulation tool, receiving as inputs the engine operating parameters, and producing as outputs the resulting emission levels and fuel consumption. The ANN outputs were then used to evaluate the objective function of the optimization process, which was performed with a GA approach. The combination of ANN and GA for the optimization of two different engine operating conditions was analyzed and important reductions in emissions and fuel consumption were reached, while also keeping the computational times low